{"as_of":"2026-08-09T21:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b7f6c3c36c54afb7e85e547faa91e5bdc9af46839deffc1a4e05e9b529589bdc","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:01:43.752801Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T23:48:24.596404Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.22480","last_updated":"2024-10-29T19:17:55Z","snapshot_observed_at":"2026-08-08T14:46:58.049897Z","submitted_at":"2024-10-29T19:17:55Z","title":"Scaling LLM Inference with Optimized Sample Compute Allocation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22480","snapshot_observed_at":"2026-08-08T20:01:43.752801Z","title":"Y ., and Li, L","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05234","last_updated":"2025-06-16T06:53:48Z","snapshot_observed_at":"2026-08-09T00:43:26.676197Z","submitted_at":"2025-02-07T19:35:25Z","title":"Optimizing Temperature for Language Models with Multi-Sample Inference","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T20:01:43.752801Z"},"links":{"cited_paper":"/paper/2410.22480","citing_paper":"/paper/2502.05234"},"observation_digest":"sha256:21cfa63b3c290c848b80f4af6fb080611d41c7a38823fdbb20afc698baec4663","observation_id":"44be4bd7-b343-4fcc-88ef-c5d72711207e","resolution":{"observed_at":"2026-08-08T20:01:43.752801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22480","last_updated":"2024-10-29T19:17:55Z","snapshot_observed_at":"2026-08-08T14:46:58.049897Z","submitted_at":"2024-10-29T19:17:55Z","title":"Scaling LLM Inference with Optimized Sample Compute Allocation","version":1},"cited_work":{"arxiv_id":"2410.22480","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.22480","snapshot_observed_at":"2026-08-06T23:48:24.596404Z","title":"Scaling LLM Inference with Optimized Sample Compute Allocation","venue":"cs.CL","work_id":"b5701473-aae2-4bce-a8fb-8dc3d26fd542","year":2024},"citing_paper":{"arxiv_id":"2506.16043","last_updated":"2025-06-19T05:40:54Z","snapshot_observed_at":"2026-08-08T14:46:38.823120Z","submitted_at":"2025-06-19T05:40:54Z","title":"DynScaling: Efficient Verifier-free Inference Scaling via Dynamic and Integrated Sampling","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:48:23.760554Z"},"links":{"cited_paper":"/paper/2410.22480","citing_paper":"/paper/2506.16043"},"observation_digest":"sha256:db44b8d24847f9485715375fecca1563daad2bd668d6a020faffb69f347df91e","observation_id":"28fef33b-21e1-4d66-8a7b-351a7232b1c6","resolution":{"observed_at":"2026-08-06T23:48:24.675376Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22480","last_updated":"2024-10-29T19:17:55Z","snapshot_observed_at":"2026-08-08T14:46:58.049897Z","submitted_at":"2024-10-29T19:17:55Z","title":"Scaling LLM Inference with Optimized Sample Compute Allocation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22480","snapshot_observed_at":"2026-08-04T18:37:58.966197Z","title":"Scaling llm inference with optimized sample compute allocation.arXiv preprint arXiv:2410.22480,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.09864","last_updated":"2025-09-11T21:35:19Z","snapshot_observed_at":"2026-08-08T15:40:25.756323Z","submitted_at":"2025-09-11T21:35:19Z","title":"Latency and Token-Aware Test-Time Compute","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T18:37:58.966197Z"},"links":{"cited_paper":"/paper/2410.22480","citing_paper":"/paper/2509.09864"},"observation_digest":"sha256:8c22ea7fe0213a22cd6fb55ec25b3718b0d63e0cf3bb9b2d9e85bb036da654f4","observation_id":"558b23a1-800d-40a6-8199-930e0505f8a7","resolution":{"observed_at":"2026-08-04T18:37:58.966197Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.22480/citation-record","integrity":"/paper/2410.22480/integrity","json":"/paper/2410.22480/citation-record.json","paper":"/paper/2410.22480"},"outbound":[],"paper":{"arxiv_id":"2410.22480","last_updated":"2024-10-29T19:17:55Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T14:46:58.049897Z","submitted_at":"2024-10-29T19:17:55Z","title":"Scaling LLM Inference with Optimized Sample Compute Allocation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.22480."}